| // Copyright (c) Facebook, Inc. and its affiliates. |
| // All rights reserved. |
| // |
| // Copyright 2019 Google LLC |
| // |
| // This source code is licensed under the BSD-style license found in the |
| // LICENSE file in the root directory of this source tree. |
| |
| #include <assert.h> |
| #include <stdbool.h> |
| #include <stddef.h> |
| #include <stdint.h> |
| #include <string.h> |
| #include <math.h> |
| |
| #include <xnnpack.h> |
| #include <xnnpack/allocator.h> |
| #include <xnnpack/log.h> |
| #include <xnnpack/math.h> |
| #include <xnnpack/operator.h> |
| #include <xnnpack/pack.h> |
| #include <xnnpack/params-init.h> |
| #include <xnnpack/params.h> |
| |
| |
| static enum xnn_status create_fully_connected_nc( |
| size_t input_channels, |
| size_t output_channels, |
| size_t input_stride, |
| size_t output_stride, |
| const void* kernel, |
| const void* bias, |
| uint32_t flags, |
| uint32_t log2_filter_element_size, |
| uint32_t bias_element_size, |
| xnn_pack_gemm_io_w_function pack_gemm_io_w, |
| xnn_pack_gemm_goi_w_function pack_gemm_goi_w, |
| const void* packing_params, |
| int packed_weights_padding_byte, |
| const void* params, |
| size_t params_size, |
| const struct gemm_parameters* gemm_parameters, |
| const struct gemm_fused_ukernels* gemm_ukernels, |
| enum xnn_operator_type operator_type, |
| xnn_operator_t* fully_connected_op_out) |
| { |
| xnn_operator_t fully_connected_op = NULL; |
| enum xnn_status status = xnn_status_uninitialized; |
| |
| if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) { |
| xnn_log_error("failed to create %s operator: XNNPACK is not initialized", |
| xnn_operator_type_to_string(operator_type)); |
| goto error; |
| } |
| |
| status = xnn_status_invalid_parameter; |
| |
| if (input_channels == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %zu input channels: number of channels must be non-zero", |
| xnn_operator_type_to_string(operator_type), input_channels); |
| goto error; |
| } |
| |
| if (output_channels == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %zu output channels: number of channels must be non-zero", |
| xnn_operator_type_to_string(operator_type), output_channels); |
| goto error; |
| } |
| |
| if (input_stride < input_channels) { |
| xnn_log_error( |
| "failed to create %s operator with input element stride of %zu: " |
| "stride must be at least as large as the number of input channels (%zu)", |
| xnn_operator_type_to_string(operator_type), input_stride, input_channels); |
| goto error; |
| } |
| |
| if (output_stride < output_channels) { |
| xnn_log_error( |
| "failed to create %s operator with output element stride of %zu: " |
| "stride must be at least as large as the number of output channels (%zu)", |
| xnn_operator_type_to_string(operator_type), output_stride, output_channels); |
| goto error; |
| } |
| |
| status = xnn_status_out_of_memory; |
| |
| fully_connected_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
| if (fully_connected_op == NULL) { |
| xnn_log_error( |
| "failed to allocate %zu bytes for %s operator descriptor", |
| sizeof(struct xnn_operator), xnn_operator_type_to_string(operator_type)); |
| goto error; |
| } |
| |
| const uint32_t nr = gemm_parameters->nr; |
| const uint32_t kr = UINT32_C(1) << gemm_parameters->log2_kr; |
| const uint32_t sr = UINT32_C(1) << gemm_parameters->log2_sr; |
| |
| const size_t n_stride = round_up(output_channels, nr); |
| const size_t k_stride = round_up_po2(input_channels, kr); |
| |
| const size_t packed_weights_size = n_stride * (bias_element_size + (k_stride << log2_filter_element_size)); |
| fully_connected_op->packed_weights = xnn_allocate_simd_memory(packed_weights_size); |
| if (fully_connected_op->packed_weights == NULL) { |
| xnn_log_error( |
| "failed to allocate %zu bytes for %s operator packed weights", |
| packed_weights_size, xnn_operator_type_to_string(operator_type)); |
| goto error; |
| } |
| memset(fully_connected_op->packed_weights, packed_weights_padding_byte, packed_weights_size); |
| |
| if (flags & XNN_FLAG_TRANSPOSE_WEIGHTS) { |
| pack_gemm_io_w( |
| output_channels, input_channels, |
| nr, kr, sr, |
| kernel, bias, |
| fully_connected_op->packed_weights, |
| packing_params); |
| } else { |
| pack_gemm_goi_w( |
| 1, output_channels, input_channels, |
| nr, kr, sr, |
| kernel, bias, |
| fully_connected_op->packed_weights, |
| packing_params); |
| } |
| |
| fully_connected_op->group_input_channels = input_channels; |
| fully_connected_op->group_output_channels = output_channels; |
| fully_connected_op->input_pixel_stride = input_stride; |
| fully_connected_op->output_pixel_stride = output_stride; |
| |
| memcpy(&fully_connected_op->params, params, params_size); |
| fully_connected_op->type = operator_type; |
| |
| fully_connected_op->ukernel.type = xnn_ukernel_type_gemm; |
| fully_connected_op->ukernel.gemm = (struct xnn_ukernel_gemm) { |
| .general_case = gemm_ukernels->gemm, |
| .mr1_case = gemm_ukernels->gemm1, |
| .mr = gemm_parameters->mr, |
| .nr = nr, |
| .kr = kr, |
| }; |
| |
| fully_connected_op->state = xnn_run_state_invalid; |
| |
| *fully_connected_op_out = fully_connected_op; |
| return xnn_status_success; |
| |
| error: |
| xnn_delete_operator(fully_connected_op); |
| return status; |
| } |
| |
| static enum xnn_status setup_fully_connected_nc( |
| xnn_operator_t fully_connected_op, |
| size_t batch_size, |
| const void* input, |
| void* output, |
| uint32_t log2_input_element_size, |
| uint32_t log2_filter_element_size, |
| uint32_t bias_element_size, |
| uint32_t log2_output_element_size, |
| const void* params, |
| size_t params_size, |
| size_t num_threads) |
| { |
| fully_connected_op->state = xnn_run_state_invalid; |
| |
| if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) { |
| xnn_log_error("failed to setup %s operator: XNNPACK is not initialized", |
| xnn_operator_type_to_string(fully_connected_op->type)); |
| return xnn_status_uninitialized; |
| } |
| |
| if (batch_size == 0) { |
| fully_connected_op->state = xnn_run_state_skip; |
| return xnn_status_success; |
| } |
| |
| fully_connected_op->batch_size = 1; |
| fully_connected_op->input_height = batch_size; |
| fully_connected_op->input_width = 1; |
| fully_connected_op->input = input; |
| |
| fully_connected_op->output_height = batch_size; |
| fully_connected_op->output_width = 1; |
| fully_connected_op->output = output; |
| |
| const size_t input_channels = fully_connected_op->group_input_channels; |
| const size_t output_channels = fully_connected_op->group_output_channels; |
| |
| uint32_t mr = fully_connected_op->ukernel.gemm.mr; |
| const uint32_t nr = fully_connected_op->ukernel.gemm.nr; |
| |
| struct xnn_hmp_gemm_ukernel gemm_ukernel = fully_connected_op->ukernel.gemm.general_case; |
| if (batch_size == 1 && fully_connected_op->ukernel.gemm.mr1_case.function[XNN_UARCH_DEFAULT] != NULL) { |
| gemm_ukernel = fully_connected_op->ukernel.gemm.mr1_case; |
| mr = 1; |
| } |
| |
| fully_connected_op->context.gemm = (struct gemm_context) { |
| .k_scaled = input_channels << log2_input_element_size, |
| .w_stride = (round_up_po2(input_channels, fully_connected_op->ukernel.gemm.kr) << log2_input_element_size) + bias_element_size, |
| .a = input, |
| .a_stride = fully_connected_op->input_pixel_stride << log2_input_element_size, |
| .packed_w = fully_connected_op->packed_weights, |
| .c = output, |
| .cm_stride = fully_connected_op->output_pixel_stride << log2_output_element_size, |
| .cn_stride = nr << log2_output_element_size, |
| .log2_csize = log2_output_element_size, |
| .ukernel = gemm_ukernel, |
| }; |
| memcpy(&fully_connected_op->context.gemm.params, params, params_size); |
| |
| size_t nc = output_channels; |
| if (num_threads > 1) { |
| const size_t num_other_tiles = divide_round_up(batch_size, mr); |
| const size_t target_tiles_per_thread = 5; |
| const size_t max_nc = divide_round_up(output_channels * num_other_tiles, num_threads * target_tiles_per_thread); |
| if (max_nc < nc) { |
| nc = min(nc, divide_round_up(nc, max_nc * nr) * nr); |
| } |
| } |
| fully_connected_op->compute.type = xnn_parallelization_type_2d_tile_2d; |
| fully_connected_op->compute.task_2d_tile_2d = (pthreadpool_task_2d_tile_2d_t) xnn_compute_gemm; |
| fully_connected_op->compute.range[0] = batch_size; |
| fully_connected_op->compute.range[1] = output_channels; |
| fully_connected_op->compute.tile[0] = mr; |
| fully_connected_op->compute.tile[1] = nc; |
| fully_connected_op->state = xnn_run_state_ready; |
| |
| return xnn_status_success; |
| } |
| |
| enum xnn_status xnn_create_fully_connected_nc_q8( |
| size_t input_channels, |
| size_t output_channels, |
| size_t input_stride, |
| size_t output_stride, |
| uint8_t input_zero_point, |
| float input_scale, |
| uint8_t kernel_zero_point, |
| float kernel_scale, |
| const uint8_t* kernel, |
| const int32_t* bias, |
| uint8_t output_zero_point, |
| float output_scale, |
| uint8_t output_min, |
| uint8_t output_max, |
| uint32_t flags, |
| xnn_operator_t* fully_connected_op_out) |
| { |
| if (input_scale <= 0.0f || !isnormal(input_scale)) { |
| xnn_log_error( |
| "failed to create %s operator with %.7g input scale: scale must be finite, normalized, and positive", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_q8), input_scale); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (kernel_scale <= 0.0f || !isnormal(kernel_scale)) { |
| xnn_log_error( |
| "failed to create %s operator with %.7g kernel scale: scale must be finite, normalized, and positive", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_q8), kernel_scale); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (output_scale <= 0.0f || !isnormal(output_scale)) { |
| xnn_log_error( |
| "failed to create %s operator with %.7g output scale: scale must be finite, normalized, and positive", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_q8), output_scale); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (output_min >= output_max) { |
| xnn_log_error( |
| "failed to create %s operator with [%" PRIu8 ", %" PRIu8 "] output range: range min must be below range max", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_q8), output_min, output_max); |
| return xnn_status_invalid_parameter; |
| } |
| |
| const float requantization_scale = input_scale * kernel_scale / output_scale; |
| if (requantization_scale >= 1.0f) { |
| xnn_log_error( |
| "failed to create %s operator with %.7g input scale, %.7g kernel scale, and %.7g output scale: " |
| "requantization scale %.7g is greater or equal to 1.0", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_q8), |
| input_scale, kernel_scale, output_scale, requantization_scale); |
| return xnn_status_unsupported_parameter; |
| } |
| |
| const union xnn_q8_gemm_params params = xnn_init_q8_gemm_params( |
| input_zero_point, kernel_zero_point, requantization_scale, output_zero_point, output_min, output_max); |
| const struct xnn_q8_packing_params packing_params = { |
| .input_zero_point = input_zero_point, |
| .kernel_zero_point = kernel_zero_point, |
| }; |
| return create_fully_connected_nc( |
| input_channels, output_channels, |
| input_stride, output_stride, |
| kernel, bias, flags, |
| sizeof(int32_t) /* sizeof(bias element) */, |
| 0 /* log2(sizeof(filter element)) = log2(sizeof(uint8_t)) */, |
| (xnn_pack_gemm_io_w_function) xnn_pack_q8_gemm_io_w, |
| (xnn_pack_gemm_goi_w_function) xnn_pack_q8_gemm_goi_w, |
| &packing_params /* packing params */, kernel_zero_point /* packed weights padding byte */, |
| ¶ms, sizeof(params), |
| &xnn_params.q8.gemm, &xnn_params.q8.gemm.minmax, |
| xnn_operator_type_fully_connected_nc_q8, |
| fully_connected_op_out); |
| } |
| |
| enum xnn_status xnn_create_fully_connected_nc_f32( |
| size_t input_channels, |
| size_t output_channels, |
| size_t input_stride, |
| size_t output_stride, |
| const float* kernel, |
| const float* bias, |
| float output_min, |
| float output_max, |
| uint32_t flags, |
| xnn_operator_t* fully_connected_op_out) |
| { |
| if (isnan(output_min)) { |
| xnn_log_error( |
| "failed to create %s operator with NaN output lower bound: lower bound must be non-NaN", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f32)); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (isnan(output_max)) { |
| xnn_log_error( |
| "failed to create %s operator with NaN output upper bound: upper bound must be non-NaN", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f32)); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (output_min >= output_max) { |
| xnn_log_error( |
| "failed to create %s operator with [%.7g, %.7g] output range: lower bound must be below upper bound", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f32), output_min, output_max); |
| return xnn_status_invalid_parameter; |
| } |
| |
| const struct gemm_fused_ukernels* gemm_ukernels = &xnn_params.f32.gemm.minmax; |
| const bool linear_activation = (output_max == INFINITY) && (output_min == -output_max); |
| if (linear_activation && xnn_params.f32.gemm.linear.gemm.function[XNN_UARCH_DEFAULT] != NULL) { |
| gemm_ukernels = &xnn_params.f32.gemm.linear; |
| } |
| |
| const union xnn_f32_minmax_params params = xnn_init_f32_minmax_params(output_min, output_max); |
| return create_fully_connected_nc( |
| input_channels, output_channels, |
| input_stride, output_stride, |
| kernel, bias, flags, |
| sizeof(float) /* sizeof(bias element) */, |
| 2 /* log2(sizeof(filter element)) = log2(sizeof(float)) */, |
| (xnn_pack_gemm_io_w_function) xnn_pack_f32_gemm_io_w, |
| (xnn_pack_gemm_goi_w_function) xnn_pack_f32_gemm_goi_w, |
| NULL /* packing params */, 0 /* packed weights padding byte */, |
| ¶ms, sizeof(params), |
| &xnn_params.f32.gemm, gemm_ukernels, |
| xnn_operator_type_fully_connected_nc_f32, |
| fully_connected_op_out); |
| } |
| |
| enum xnn_status xnn_setup_fully_connected_nc_q8( |
| xnn_operator_t fully_connected_op, |
| size_t batch_size, |
| const uint8_t* input, |
| uint8_t* output, |
| pthreadpool_t threadpool) |
| { |
| if (fully_connected_op->type != xnn_operator_type_fully_connected_nc_q8) { |
| xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_q8), |
| xnn_operator_type_to_string(fully_connected_op->type)); |
| return xnn_status_invalid_parameter; |
| } |
| |
| return setup_fully_connected_nc( |
| fully_connected_op, |
| batch_size, |
| input, output, |
| 0 /* log2(sizeof(input element)) = log2(sizeof(uint8_t)) */, |
| 0 /* log2(sizeof(filter element)) = log2(sizeof(uint8_t)) */, |
| sizeof(int32_t) /* sizeof(bias element) */, |
| 0 /* log2(sizeof(output element)) = log2(sizeof(uint8_t)) */, |
| &fully_connected_op->params.q8_gemm, |
| sizeof(fully_connected_op->params.q8_gemm), |
| pthreadpool_get_threads_count(threadpool)); |
| } |
| |
| enum xnn_status xnn_setup_fully_connected_nc_f32( |
| xnn_operator_t fully_connected_op, |
| size_t batch_size, |
| const float* input, |
| float* output, |
| pthreadpool_t threadpool) |
| { |
| if (fully_connected_op->type != xnn_operator_type_fully_connected_nc_f32) { |
| xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)", |
| xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f32), |
| xnn_operator_type_to_string(fully_connected_op->type)); |
| return xnn_status_invalid_parameter; |
| } |
| |
| return setup_fully_connected_nc( |
| fully_connected_op, |
| batch_size, |
| input, output, |
| 2 /* log2(sizeof(input element)) = log2(sizeof(float)) */, |
| 2 /* log2(sizeof(filter element)) = log2(sizeof(float)) */, |
| sizeof(float) /* sizeof(bias element) */, |
| 2 /* log2(sizeof(output element)) = log2(sizeof(float)) */, |
| &fully_connected_op->params.f32_minmax, |
| sizeof(fully_connected_op->params.f32_minmax), |
| pthreadpool_get_threads_count(threadpool)); |
| } |